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   &#160;<span id="projectnumber">3.4.90 (git rev 67eeba6e720c5745abc77ae6c92ce0a44aa7b7ae)</span>
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<div class="header">
  <div class="headertitle">
<div class="title">Redux.h</div>  </div>
</div><!--header-->
<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// for linear algebra.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Copyright (C) 2008 Gael Guennebaud &lt;gael.guennebaud@inria.fr&gt;</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">// Copyright (C) 2006-2008 Benoit Jacob &lt;jacob.benoit.1@gmail.com&gt;</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">// Public License v. 2.0. If a copy of the MPL was not distributed</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#ifndef EIGEN_REDUX_H</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#define EIGEN_REDUX_H</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160; </div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &quot;./InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> { </div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160; </div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160; </div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment">// TODO</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment">//  * implement other kind of vectorization</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment">//  * factorize code</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment">/***************************************************************************</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="comment">* Part 1 : the logic deciding a strategy for vectorization and unrolling</span></div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment">***************************************************************************/</span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160; </div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator&gt;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="keyword">struct </span>redux_traits</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;{</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <span class="keyword">typedef</span> <span class="keyword">typename</span> find_best_packet&lt;typename Evaluator::Scalar,Evaluator::SizeAtCompileTime&gt;::type PacketType;</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    PacketSize = unpacket_traits&lt;PacketType&gt;::size,</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    InnerMaxSize = int(Evaluator::IsRowMajor)</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;                 ? Evaluator::MaxColsAtCompileTime</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;                 : Evaluator::MaxRowsAtCompileTime,</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    OuterMaxSize = int(Evaluator::IsRowMajor)</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;                 ? Evaluator::MaxRowsAtCompileTime</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;                 : Evaluator::MaxColsAtCompileTime,</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    SliceVectorizedWork = int(InnerMaxSize)==<a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> ? <a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;                        : int(OuterMaxSize)==<a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> ? (int(InnerMaxSize)&gt;=int(PacketSize) ? <a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> : 0)</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;                        : (<span class="keywordtype">int</span>(InnerMaxSize)/int(PacketSize)) * <span class="keywordtype">int</span>(OuterMaxSize)</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;  };</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    MightVectorize = (int(Evaluator::Flags)&amp;<a class="code" href="group__flags.html#ga020f88dc24a123b9afbd756c4b220db2">ActualPacketAccessBit</a>)</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;                  &amp;&amp; (functor_traits&lt;Func&gt;::PacketAccess),</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    MayLinearVectorize = bool(MightVectorize) &amp;&amp; (int(Evaluator::Flags)&amp;<a class="code" href="group__flags.html#ga4b983a15d57cd55806df618ac544d09e">LinearAccessBit</a>),</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    MaySliceVectorize  = <span class="keywordtype">bool</span>(MightVectorize) &amp;&amp; (int(SliceVectorizedWork)==<a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> || int(SliceVectorizedWork)&gt;=3)</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  };</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160; </div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal)</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;              : int(MaySliceVectorize)  ? int(SliceVectorizedTraversal)</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;                                        : int(DefaultTraversal)</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  };</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    Cost = Evaluator::SizeAtCompileTime == <a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> ? <a class="code" href="namespaceEigen.html#a3163430a1c13173faffde69016b48aaf">HugeCost</a></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;         : int(Evaluator::SizeAtCompileTime) * int(Evaluator::CoeffReadCost) + (Evaluator::SizeAtCompileTime-1) * functor_traits&lt;Func&gt;::Cost,</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    UnrollingLimit = EIGEN_UNROLLING_LIMIT * (<span class="keywordtype">int</span>(Traversal) == int(DefaultTraversal) ? 1 : int(PacketSize))</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  };</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160; </div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    Unrolling = Cost &lt;= UnrollingLimit ? CompleteUnrolling : NoUnrolling</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  };</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  </div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="preprocessor">#ifdef EIGEN_DEBUG_ASSIGN</span></div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">void</span> debug()</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  {</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    std::cerr &lt;&lt; <span class="stringliteral">&quot;Xpr: &quot;</span> &lt;&lt; <span class="keyword">typeid</span>(<span class="keyword">typename</span> Evaluator::XprType).name() &lt;&lt; std::endl;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    std::cerr.setf(std::ios::hex, std::ios::basefield);</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    EIGEN_DEBUG_VAR(Evaluator::Flags)</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    std::cerr.unsetf(std::ios::hex);</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    EIGEN_DEBUG_VAR(InnerMaxSize)</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    EIGEN_DEBUG_VAR(OuterMaxSize)</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    EIGEN_DEBUG_VAR(SliceVectorizedWork)</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    EIGEN_DEBUG_VAR(PacketSize)</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    EIGEN_DEBUG_VAR(MightVectorize)</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    EIGEN_DEBUG_VAR(MayLinearVectorize)</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    EIGEN_DEBUG_VAR(MaySliceVectorize)</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    std::cerr &lt;&lt; <span class="stringliteral">&quot;Traversal&quot;</span> &lt;&lt; <span class="stringliteral">&quot; = &quot;</span> &lt;&lt; Traversal &lt;&lt; <span class="stringliteral">&quot; (&quot;</span> &lt;&lt; demangle_traversal(Traversal) &lt;&lt; <span class="stringliteral">&quot;)&quot;</span> &lt;&lt; std::endl;</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    EIGEN_DEBUG_VAR(UnrollingLimit)</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    std::cerr &lt;&lt; <span class="stringliteral">&quot;Unrolling&quot;</span> &lt;&lt; <span class="stringliteral">&quot; = &quot;</span> &lt;&lt; Unrolling &lt;&lt; <span class="stringliteral">&quot; (&quot;</span> &lt;&lt; demangle_unrolling(Unrolling) &lt;&lt; <span class="stringliteral">&quot;)&quot;</span> &lt;&lt; std::endl;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    std::cerr &lt;&lt; std::endl;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  }</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;};</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;<span class="comment">/***************************************************************************</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="comment">* Part 2 : unrollers</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;<span class="comment">***************************************************************************/</span></div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="comment">/*** no vectorization ***/</span></div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160; </div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Start, <span class="keywordtype">int</span> Length&gt;</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;<span class="keyword">struct </span>redux_novec_unroller</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;{</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    HalfLength = Length/2</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  };</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160; </div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160; </div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func)</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  {</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="keywordflow">return</span> func(redux_novec_unroller&lt;Func, Evaluator, Start, HalfLength&gt;::run(eval,func),</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;                redux_novec_unroller&lt;Func, Evaluator, Start+HalfLength, Length-HalfLength&gt;::run(eval,func));</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  }</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;};</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160; </div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Start&gt;</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;<span class="keyword">struct </span>redux_novec_unroller&lt;Func, Evaluator, Start, 1&gt;</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;{</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    outer = Start / Evaluator::InnerSizeAtCompileTime,</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    inner = Start % Evaluator::InnerSizeAtCompileTime</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  };</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp;)</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  {</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="keywordflow">return</span> eval.coeffByOuterInner(outer, inner);</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  }</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;};</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="comment">// This is actually dead code and will never be called. It is required</span></div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;<span class="comment">// to prevent false warnings regarding failed inlining though</span></div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;<span class="comment">// for 0 length run() will never be called at all.</span></div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Start&gt;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;<span class="keyword">struct </span>redux_novec_unroller&lt;Func, Evaluator, Start, 0&gt;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;{</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  EIGEN_DEVICE_FUNC </div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <span class="keyword">static</span> EIGEN_STRONG_INLINE Scalar run(<span class="keyword">const</span> Evaluator&amp;, <span class="keyword">const</span> Func&amp;) { <span class="keywordflow">return</span> Scalar(); }</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;};</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;<span class="comment">/*** vectorization ***/</span></div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160; </div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Start, <span class="keywordtype">int</span> Length&gt;</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;<span class="keyword">struct </span>redux_vec_unroller</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;{</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> PacketType&gt;</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;  EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;  <span class="keyword">static</span> EIGEN_STRONG_INLINE PacketType run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func)</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  {</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      PacketSize = unpacket_traits&lt;PacketType&gt;::size,</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;      HalfLength = Length/2</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    };</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    <span class="keywordflow">return</span> func.packetOp(</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;            redux_vec_unroller&lt;Func, Evaluator, Start, HalfLength&gt;::template run&lt;PacketType&gt;(eval,func),</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;            redux_vec_unroller&lt;Func, Evaluator, Start+HalfLength, Length-HalfLength&gt;::template run&lt;PacketType&gt;(eval,func) );</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  }</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;};</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160; </div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Start&gt;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;<span class="keyword">struct </span>redux_vec_unroller&lt;Func, Evaluator, Start, 1&gt;</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;{</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> PacketType&gt;</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;  <span class="keyword">static</span> EIGEN_STRONG_INLINE PacketType run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp;)</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  {</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;      PacketSize = unpacket_traits&lt;PacketType&gt;::size,</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;      index = Start * PacketSize,</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;      outer = index / int(Evaluator::InnerSizeAtCompileTime),</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;      inner = index % int(Evaluator::InnerSizeAtCompileTime),</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;      alignment = Evaluator::Alignment</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    };</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    <span class="keywordflow">return</span> eval.template packetByOuterInner&lt;alignment,PacketType&gt;(outer, inner);</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  }</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;};</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160; </div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;<span class="comment">/***************************************************************************</span></div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;<span class="comment">* Part 3 : implementation of all cases</span></div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;<span class="comment">***************************************************************************/</span></div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160; </div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator,</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;         <span class="keywordtype">int</span> Traversal = redux_traits&lt;Func, Evaluator&gt;::Traversal,</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;         <span class="keywordtype">int</span> Unrolling = redux_traits&lt;Func, Evaluator&gt;::Unrolling</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;&gt;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;<span class="keyword">struct </span>redux_impl;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160; </div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator&gt;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;<span class="keyword">struct </span>redux_impl&lt;Func, Evaluator, DefaultTraversal, NoUnrolling&gt;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;{</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160; </div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  EIGEN_DEVICE_FUNC <span class="keyword">static</span> EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;  Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func, <span class="keyword">const</span> XprType&amp; xpr)</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  {</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    eigen_assert(xpr.rows()&gt;0 &amp;&amp; xpr.cols()&gt;0 &amp;&amp; <span class="stringliteral">&quot;you are using an empty matrix&quot;</span>);</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    Scalar res;</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    res = eval.coeffByOuterInner(0, 0);</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = 1; i &lt; xpr.innerSize(); ++i)</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;      res = func(res, eval.coeffByOuterInner(0, i));</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i = 1; i &lt; xpr.outerSize(); ++i)</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> j = 0; j &lt; xpr.innerSize(); ++j)</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        res = func(res, eval.coeffByOuterInner(i, j));</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    <span class="keywordflow">return</span> res;</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;  }</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;};</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator&gt;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="keyword">struct </span>redux_impl&lt;Func,Evaluator, DefaultTraversal, CompleteUnrolling&gt;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;  : redux_novec_unroller&lt;Func,Evaluator, 0, Evaluator::SizeAtCompileTime&gt;</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;{</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  <span class="keyword">typedef</span> redux_novec_unroller&lt;Func,Evaluator, 0, Evaluator::SizeAtCompileTime&gt; Base;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  EIGEN_DEVICE_FUNC <span class="keyword">static</span> EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func, <span class="keyword">const</span> XprType&amp; <span class="comment">/*xpr*/</span>)</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  {</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    <span class="keywordflow">return</span> Base::run(eval,func);</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  }</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;};</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator&gt;</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;<span class="keyword">struct </span>redux_impl&lt;Func, Evaluator, LinearVectorizedTraversal, NoUnrolling&gt;</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;{</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> redux_traits&lt;Func, Evaluator&gt;::PacketType PacketScalar;</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160; </div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;  <span class="keyword">static</span> Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func, <span class="keyword">const</span> XprType&amp; xpr)</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;  {</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> size = xpr.size();</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    </div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> packetSize = redux_traits&lt;Func, Evaluator&gt;::PacketSize;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> packetAlignment = unpacket_traits&lt;PacketScalar&gt;::alignment;</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;      alignment0 = (bool(Evaluator::Flags &amp; <a class="code" href="group__flags.html#gabf1e9d0516a933445a4c307ad8f14915">DirectAccessBit</a>) &amp;&amp; bool(packet_traits&lt;Scalar&gt;::AlignedOnScalar)) ? <span class="keywordtype">int</span>(packetAlignment) : int(<a class="code" href="group__enums.html#gga45fe06e29902b7a2773de05ba27b47a1a4e19dd09d5ff42295ba1d72d12a46686">Unaligned</a>),</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;      alignment = plain_enum_max(alignment0, Evaluator::Alignment)</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    };</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> alignedStart = internal::first_default_aligned(xpr);</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> alignedEnd2 = alignedStart + alignedSize2;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> alignedEnd  = alignedStart + alignedSize;</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    Scalar res;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <span class="keywordflow">if</span>(alignedSize)</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    {</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;      PacketScalar packet_res0 = eval.template packet&lt;alignment,PacketScalar&gt;(alignedStart);</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;      <span class="keywordflow">if</span>(alignedSize&gt;packetSize) <span class="comment">// we have at least two packets to partly unroll the loop</span></div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;      {</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        PacketScalar packet_res1 = eval.template packet&lt;alignment,PacketScalar&gt;(alignedStart+packetSize);</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;        <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> index = alignedStart + 2*packetSize; index &lt; alignedEnd2; index += 2*packetSize)</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        {</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;          packet_res0 = func.packetOp(packet_res0, eval.template packet&lt;alignment,PacketScalar&gt;(index));</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;          packet_res1 = func.packetOp(packet_res1, eval.template packet&lt;alignment,PacketScalar&gt;(index+packetSize));</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        }</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160; </div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        packet_res0 = func.packetOp(packet_res0,packet_res1);</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;        <span class="keywordflow">if</span>(alignedEnd&gt;alignedEnd2)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;          packet_res0 = func.packetOp(packet_res0, eval.template packet&lt;alignment,PacketScalar&gt;(alignedEnd2));</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;      }</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;      res = func.predux(packet_res0);</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160; </div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> index = 0; index &lt; alignedStart; ++index)</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        res = func(res,eval.coeff(index));</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160; </div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> index = alignedEnd; index &lt; size; ++index)</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        res = func(res,eval.coeff(index));</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    }</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;    <span class="keywordflow">else</span> <span class="comment">// too small to vectorize anything.</span></div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;         <span class="comment">// since this is dynamic-size hence inefficient anyway for such small sizes, don&#39;t try to optimize.</span></div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    {</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;      res = eval.coeff(0);</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> index = 1; index &lt; size; ++index)</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        res = func(res,eval.coeff(index));</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    }</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    <span class="keywordflow">return</span> res;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  }</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;};</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160; </div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;<span class="comment">// NOTE: for SliceVectorizedTraversal we simply bypass unrolling</span></div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator, <span class="keywordtype">int</span> Unrolling&gt;</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;<span class="keyword">struct </span>redux_impl&lt;Func, Evaluator, SliceVectorizedTraversal, Unrolling&gt;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;{</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> redux_traits&lt;Func, Evaluator&gt;::PacketType PacketType;</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160; </div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;  EIGEN_DEVICE_FUNC <span class="keyword">static</span> Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func, <span class="keyword">const</span> XprType&amp; xpr)</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;  {</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    eigen_assert(xpr.rows()&gt;0 &amp;&amp; xpr.cols()&gt;0 &amp;&amp; <span class="stringliteral">&quot;you are using an empty matrix&quot;</span>);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> innerSize = xpr.innerSize();</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> outerSize = xpr.outerSize();</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;    <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;      packetSize = redux_traits&lt;Func, Evaluator&gt;::PacketSize</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    };</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    <span class="keyword">const</span> <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> packetedInnerSize = ((innerSize)/packetSize)*packetSize;</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    Scalar res;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    <span class="keywordflow">if</span>(packetedInnerSize)</div>
<div class="line"><a name="l00306"></a><span class="lineno"><a class="line" href="classEigen_1_1MatrixBase.html#a544b609f65eb2bd3e368b3fc2d79479e">  306</a></span>&#160;    {</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;      PacketType packet_res = eval.template packet&lt;Unaligned,PacketType&gt;(0,0);</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> j=0; j&lt;outerSize; ++j)</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;        <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i=(j==0?packetSize:0); i&lt;packetedInnerSize; i+=<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>(packetSize))</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;          packet_res = func.packetOp(packet_res, eval.template packetByOuterInner&lt;Unaligned,PacketType&gt;(j,i));</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160; </div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;      res = func.predux(packet_res);</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;      <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> j=0; j&lt;outerSize; ++j)</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;        <span class="keywordflow">for</span>(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> i=packetedInnerSize; i&lt;innerSize; ++i)</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;          res = func(res, eval.coeffByOuterInner(j,i));</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    }</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;    <span class="keywordflow">else</span> <span class="comment">// too small to vectorize anything.</span></div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;         <span class="comment">// since this is dynamic-size hence inefficient anyway for such small sizes, don&#39;t try to optimize.</span></div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    {</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;      res = redux_impl&lt;Func, Evaluator, DefaultTraversal, NoUnrolling&gt;::run(eval, func, xpr);</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    }</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160; </div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <span class="keywordflow">return</span> res;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;  }</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;};</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160; </div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func, <span class="keyword">typename</span> Evaluator&gt;</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;<span class="keyword">struct </span>redux_impl&lt;Func, Evaluator, LinearVectorizedTraversal, CompleteUnrolling&gt;</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;{</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Evaluator::Scalar Scalar;</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160; </div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> redux_traits&lt;Func, Evaluator&gt;::PacketType PacketType;</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    PacketSize = redux_traits&lt;Func, Evaluator&gt;::PacketSize,</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    Size = Evaluator::SizeAtCompileTime,</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    VectorizedSize = (int(Size) / int(PacketSize)) * <span class="keywordtype">int</span>(PacketSize)</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;  };</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160; </div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;  <span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType&gt;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;  EIGEN_DEVICE_FUNC <span class="keyword">static</span> EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;  Scalar run(<span class="keyword">const</span> Evaluator &amp;eval, <span class="keyword">const</span> Func&amp; func, <span class="keyword">const</span> XprType &amp;xpr)</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;  {</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    EIGEN_ONLY_USED_FOR_DEBUG(xpr)</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    eigen_assert(xpr.rows()&gt;0 &amp;&amp; xpr.cols()&gt;0 &amp;&amp; <span class="stringliteral">&quot;you are using an empty matrix&quot;</span>);</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;    <span class="keywordflow">if</span> (VectorizedSize &gt; 0) {</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      Scalar res = func.predux(redux_vec_unroller&lt;Func, Evaluator, 0, Size / PacketSize&gt;::template run&lt;PacketType&gt;(eval,func));</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;      <span class="keywordflow">if</span> (VectorizedSize != Size)</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        res = func(res,redux_novec_unroller&lt;Func, Evaluator, VectorizedSize, Size-VectorizedSize&gt;::run(eval,func));</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;      <span class="keywordflow">return</span> res;</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    }</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;      <span class="keywordflow">return</span> redux_novec_unroller&lt;Func, Evaluator, 0, Size&gt;::run(eval,func);</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    }</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;  }</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;};</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160; </div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;<span class="comment">// evaluator adaptor</span></div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> XprType_&gt;</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;<span class="keyword">class </span>redux_evaluator : <span class="keyword">public</span> internal::evaluator&lt;XprType_&gt;</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;{</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;  <span class="keyword">typedef</span> internal::evaluator&lt;XprType_&gt; Base;</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;  <span class="keyword">typedef</span> XprType_ XprType;</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;  <span class="keyword">explicit</span> redux_evaluator(<span class="keyword">const</span> XprType &amp;xpr) : Base(xpr) {}</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;  </div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Scalar Scalar;</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::PacketScalar PacketScalar;</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;  </div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime,</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    MaxColsAtCompileTime = XprType::MaxColsAtCompileTime,</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;    <span class="comment">// TODO we should not remove DirectAccessBit and rather find an elegant way to query the alignment offset at runtime from the evaluator</span></div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    Flags = Base::Flags &amp; ~<a class="code" href="group__flags.html#gabf1e9d0516a933445a4c307ad8f14915">DirectAccessBit</a>,</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;    IsRowMajor = XprType::IsRowMajor,</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;    SizeAtCompileTime = XprType::SizeAtCompileTime,</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;    InnerSizeAtCompileTime = XprType::InnerSizeAtCompileTime</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;  };</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;  </div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;  CoeffReturnType coeffByOuterInner(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> outer, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inner)<span class="keyword"> const</span></div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;<span class="keyword">  </span>{ <span class="keywordflow">return</span> Base::coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;  </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;  <span class="keyword">template</span>&lt;<span class="keywordtype">int</span> LoadMode, <span class="keyword">typename</span> PacketType&gt;</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;  PacketType packetByOuterInner(<a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> outer, <a class="code" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> inner)<span class="keyword"> const</span></div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;<span class="keyword">  </span>{ <span class="keywordflow">return</span> Base::template packet&lt;LoadMode,PacketType&gt;(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;  </div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;};</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160; </div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;} <span class="comment">// end namespace internal</span></div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160; </div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;<span class="comment">/***************************************************************************</span></div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;<span class="comment">* Part 4 : public API</span></div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;<span class="comment">***************************************************************************/</span></div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160; </div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160; </div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Func&gt;</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00411"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a63ce1e4fab36bff43bbadcdd06a67724">  411</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html">DenseBase&lt;Derived&gt;::redux</a>(<span class="keyword">const</span> Func&amp; func)<span class="keyword"> const</span></div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;  eigen_assert(this-&gt;rows()&gt;0 &amp;&amp; this-&gt;cols()&gt;0 &amp;&amp; <span class="stringliteral">&quot;you are using an empty matrix&quot;</span>);</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160; </div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> internal::redux_evaluator&lt;Derived&gt; ThisEvaluator;</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;  ThisEvaluator thisEval(derived());</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160; </div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;  <span class="comment">// The initial expression is passed to the reducer as an additional argument instead of</span></div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;  <span class="comment">// passing it as a member of redux_evaluator to help  </span></div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;  <span class="keywordflow">return</span> internal::redux_impl&lt;Func, ThisEvaluator&gt;::run(thisEval, func, derived());</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;}</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160; </div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;<span class="keyword">template</span>&lt;<span class="keywordtype">int</span> NaNPropagation&gt;</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00433"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a0739f9c868c331031c7810e21838dcb2">  433</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html#a0739f9c868c331031c7810e21838dcb2">DenseBase&lt;Derived&gt;::minCoeff</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00435"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#addd7080d5c202795820e361768d0140c">  435</a></span>&#160;  <span class="keywordflow">return</span> derived().redux(Eigen::internal::scalar_min_op&lt;Scalar,Scalar, NaNPropagation&gt;());</div>
<div class="line"><a name="l00436"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a21ac6c0419a72ad7a88ea0bc189017d7">  436</a></span>&#160;}</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160; </div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;<span class="keyword">template</span>&lt;<span class="keywordtype">int</span> NaNPropagation&gt;</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00448"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a7e6987d106f1cca3ac6ab36d288cc8e1">  448</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html#a7e6987d106f1cca3ac6ab36d288cc8e1">DenseBase&lt;Derived&gt;::maxCoeff</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;  <span class="keywordflow">return</span> derived().redux(Eigen::internal::scalar_max_op&lt;Scalar,Scalar, NaNPropagation&gt;());</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;}</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160; </div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00461"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#addd7080d5c202795820e361768d0140c">  461</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html#addd7080d5c202795820e361768d0140c">DenseBase&lt;Derived&gt;::sum</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;  <span class="keywordflow">if</span>(SizeAtCompileTime==0 || (SizeAtCompileTime==<a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> &amp;&amp; size()==0))</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="classEigen_1_1DenseBase.html#a5feed465b3a8e60c47e73ecce83e39a2">Scalar</a>(0);</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;  <span class="keywordflow">return</span> derived().redux(Eigen::internal::scalar_sum_op&lt;Scalar,Scalar&gt;());</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;}</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160; </div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00474"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#a21ac6c0419a72ad7a88ea0bc189017d7">  474</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html#a21ac6c0419a72ad7a88ea0bc189017d7">DenseBase&lt;Derived&gt;::mean</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;<span class="preprocessor">#ifdef __INTEL_COMPILER</span></div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;<span class="preprocessor">  #pragma warning push</span></div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;<span class="preprocessor">  #pragma warning ( disable : 2259 )</span></div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classEigen_1_1DenseBase.html#a5feed465b3a8e60c47e73ecce83e39a2">Scalar</a>(derived().redux(Eigen::internal::scalar_sum_op&lt;Scalar,Scalar&gt;())) / <a class="code" href="classEigen_1_1DenseBase.html#a5feed465b3a8e60c47e73ecce83e39a2">Scalar</a>(this-&gt;size());</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;<span class="preprocessor">#ifdef __INTEL_COMPILER</span></div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;<span class="preprocessor">  #pragma warning pop</span></div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;}</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160; </div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00495"></a><span class="lineno"><a class="line" href="classEigen_1_1DenseBase.html#af119d9a4efe5a15cd83c1ccdf01b3a4f">  495</a></span>&#160;<a class="code" href="classEigen_1_1DenseBase.html#af119d9a4efe5a15cd83c1ccdf01b3a4f">DenseBase&lt;Derived&gt;::prod</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;  <span class="keywordflow">if</span>(SizeAtCompileTime==0 || (SizeAtCompileTime==<a class="code" href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Dynamic</a> &amp;&amp; size()==0))</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="classEigen_1_1DenseBase.html#a5feed465b3a8e60c47e73ecce83e39a2">Scalar</a>(1);</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;  <span class="keywordflow">return</span> derived().redux(Eigen::internal::scalar_product_op&lt;Scalar&gt;());</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;}</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160; </div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Derived&gt;</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> internal::traits&lt;Derived&gt;::Scalar</div>
<div class="line"><a name="l00510"></a><span class="lineno"><a class="line" href="classEigen_1_1MatrixBase.html#a544b609f65eb2bd3e368b3fc2d79479e">  510</a></span>&#160;<a class="code" href="classEigen_1_1MatrixBase.html#a544b609f65eb2bd3e368b3fc2d79479e">MatrixBase&lt;Derived&gt;::trace</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;  <span class="keywordflow">return</span> derived().diagonal().sum();</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;}</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160; </div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;} <span class="comment">// end namespace Eigen</span></div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160; </div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;<span class="preprocessor">#endif </span><span class="comment">// EIGEN_REDUX_H</span></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html"><div class="ttname"><a href="classEigen_1_1DenseBase.html">Eigen::DenseBase</a></div><div class="ttdoc">Base class for all dense matrices, vectors, and arrays.</div><div class="ttdef"><b>Definition:</b> DenseBase.h:42</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_a0739f9c868c331031c7810e21838dcb2"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a0739f9c868c331031c7810e21838dcb2">Eigen::DenseBase::minCoeff</a></div><div class="ttdeci">internal::traits&lt; Derived &gt;::Scalar minCoeff() const</div><div class="ttdef"><b>Definition:</b> Redux.h:433</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_a21ac6c0419a72ad7a88ea0bc189017d7"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a21ac6c0419a72ad7a88ea0bc189017d7">Eigen::DenseBase::mean</a></div><div class="ttdeci">Scalar mean() const</div><div class="ttdef"><b>Definition:</b> Redux.h:474</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_a5feed465b3a8e60c47e73ecce83e39a2"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a5feed465b3a8e60c47e73ecce83e39a2">Eigen::DenseBase::Scalar</a></div><div class="ttdeci">internal::traits&lt; Derived &gt;::Scalar Scalar</div><div class="ttdef"><b>Definition:</b> DenseBase.h:61</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_a7e6987d106f1cca3ac6ab36d288cc8e1"><div class="ttname"><a href="classEigen_1_1DenseBase.html#a7e6987d106f1cca3ac6ab36d288cc8e1">Eigen::DenseBase::maxCoeff</a></div><div class="ttdeci">internal::traits&lt; Derived &gt;::Scalar maxCoeff() const</div><div class="ttdef"><b>Definition:</b> Redux.h:448</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_addd7080d5c202795820e361768d0140c"><div class="ttname"><a href="classEigen_1_1DenseBase.html#addd7080d5c202795820e361768d0140c">Eigen::DenseBase::sum</a></div><div class="ttdeci">Scalar sum() const</div><div class="ttdef"><b>Definition:</b> Redux.h:461</div></div>
<div class="ttc" id="aclassEigen_1_1DenseBase_html_af119d9a4efe5a15cd83c1ccdf01b3a4f"><div class="ttname"><a href="classEigen_1_1DenseBase.html#af119d9a4efe5a15cd83c1ccdf01b3a4f">Eigen::DenseBase::prod</a></div><div class="ttdeci">Scalar prod() const</div><div class="ttdef"><b>Definition:</b> Redux.h:495</div></div>
<div class="ttc" id="aclassEigen_1_1MatrixBase_html_a544b609f65eb2bd3e368b3fc2d79479e"><div class="ttname"><a href="classEigen_1_1MatrixBase.html#a544b609f65eb2bd3e368b3fc2d79479e">Eigen::MatrixBase::trace</a></div><div class="ttdeci">Scalar trace() const</div><div class="ttdef"><b>Definition:</b> Redux.h:510</div></div>
<div class="ttc" id="agroup__enums_html_gga45fe06e29902b7a2773de05ba27b47a1a4e19dd09d5ff42295ba1d72d12a46686"><div class="ttname"><a href="group__enums.html#gga45fe06e29902b7a2773de05ba27b47a1a4e19dd09d5ff42295ba1d72d12a46686">Eigen::Unaligned</a></div><div class="ttdeci">@ Unaligned</div><div class="ttdef"><b>Definition:</b> Constants.h:235</div></div>
<div class="ttc" id="agroup__flags_html_ga020f88dc24a123b9afbd756c4b220db2"><div class="ttname"><a href="group__flags.html#ga020f88dc24a123b9afbd756c4b220db2">Eigen::ActualPacketAccessBit</a></div><div class="ttdeci">const unsigned int ActualPacketAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:107</div></div>
<div class="ttc" id="agroup__flags_html_ga4b983a15d57cd55806df618ac544d09e"><div class="ttname"><a href="group__flags.html#ga4b983a15d57cd55806df618ac544d09e">Eigen::LinearAccessBit</a></div><div class="ttdeci">const unsigned int LinearAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:132</div></div>
<div class="ttc" id="agroup__flags_html_gabf1e9d0516a933445a4c307ad8f14915"><div class="ttname"><a href="group__flags.html#gabf1e9d0516a933445a4c307ad8f14915">Eigen::DirectAccessBit</a></div><div class="ttdeci">const unsigned int DirectAccessBit</div><div class="ttdef"><b>Definition:</b> Constants.h:157</div></div>
<div class="ttc" id="anamespaceEigen_html"><div class="ttname"><a href="namespaceEigen.html">Eigen</a></div><div class="ttdoc">Namespace containing all symbols from the Eigen library.</div><div class="ttdef"><b>Definition:</b> Core:139</div></div>
<div class="ttc" id="anamespaceEigen_html_a3163430a1c13173faffde69016b48aaf"><div class="ttname"><a href="namespaceEigen.html#a3163430a1c13173faffde69016b48aaf">Eigen::HugeCost</a></div><div class="ttdeci">const int HugeCost</div><div class="ttdef"><b>Definition:</b> Constants.h:46</div></div>
<div class="ttc" id="anamespaceEigen_html_a62e77e0933482dafde8fe197d9a2cfde"><div class="ttname"><a href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Eigen::Index</a></div><div class="ttdeci">EIGEN_DEFAULT_DENSE_INDEX_TYPE Index</div><div class="ttdoc">The Index type as used for the API.</div><div class="ttdef"><b>Definition:</b> Meta.h:59</div></div>
<div class="ttc" id="anamespaceEigen_html_ad81fa7195215a0ce30017dfac309f0b2"><div class="ttname"><a href="namespaceEigen.html#ad81fa7195215a0ce30017dfac309f0b2">Eigen::Dynamic</a></div><div class="ttdeci">const int Dynamic</div><div class="ttdef"><b>Definition:</b> Constants.h:24</div></div>
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